Human ovarian tumors and normal ovaries
Ontology highlight
ABSTRACT:
ORGANISM(S): Homo sapiens
PROVIDER: GSE6008 | GEO | 2007/04/09
SECONDARY ACCESSION(S): PRJNA97803
REPOSITORIES: GEO
Similar Datasets
Project description:99 individual ovarian tumors (37 endometrioid, 41 serous, 13 mucinous, and 8 clear cell carcinomas) and 4 individual normal ovary samples, each assayed on an Affymetrix HG_U133A array Experiment Overall Design: 99 individual ovarian tumors (37 endometrioid, 41 serous, 13 mucinous, and 8 clear cell carcinomas) and 4 individual normal ovary samples. RNA expression was analyzed using one Affymetrix HG_U133A array per sample.
2008-06-14 | E-GEOD-6008 | biostudies-arrayexpress
Project description:We performed a genome-scale DNA methylation analysis of 41 ovarian tumors and 10 normal lymphocytic samples. We used the Illumina Infinium HumanMethylation27 Beadchip platform that interrogates the DNA methylation profiles of approximately 27,000 CpGs to identify sensitive markers for ovarian cancer detection. The 41 tumor samples included one mixed (clear cell and endometrioid) tumor, three clear cell carcinomas, four mucinous, four endometrioid, and 32 serous epithelial ovarian carcinomas. The lymphocytic DNA samples were obtained from 10 healthy older women.
2012-01-01 | GSE26989 | GEO
Project description:We performed a genome-scale DNA methylation analysis of 41 ovarian tumors and 10 normal lymphocytic samples. We used the Illumina Infinium HumanMethylation27 Beadchip platform that interrogates the DNA methylation profiles of approximately 27,000 CpGs to identify sensitive markers for ovarian cancer detection. The 41 tumor samples included one mixed (clear cell and endometrioid) tumor, three clear cell carcinomas, four mucinous, four endometrioid, and 32 serous epithelial ovarian carcinomas. The lymphocytic DNA samples were obtained from 10 healthy older women. DNA obtained from 41 ovarian cancer tissue samples and 10 peripheral blood leukocyte (PBL) samples was bisulfite converted and then hybridized to the Illumina Infinium 27k Human Methylation Beadchip v.1.2 biological replicate: sample WBC6, WBC11 biological replicate: sample WBC8, WBC12
2012-01-01 | E-GEOD-26989 | biostudies-arrayexpress
Project description:In the current study we performed epigenomic characterization of 13 different in vitro models of high-grade serous (HGSOC), low-grade serous (LGSOC), mucinous (MOC), endometrioid (ENOC) and clear cell (CCOC) carcinoma using ChIP-Seq for histone modication H3K4me1.
2024-03-18 | GSE261636 | GEO
Project description:Transcriptional profiling of 19 ovarian tumors of 5 distinct histologic types (serous, endometrioid, clear cell, mucinous and small cell), to investigate similar and distinct biology associated with each histologic type.
2014-01-17 | GSE49888 | GEO
Project description:Biomarkers for early detection of ovarian tumors are urgently needed. Tumors of the ovary grow within cysts and most are benign.Surgical sampling is the only way to ensure accurate diagnosis, but often leads to morbidity and loss of female hormones. The present study explored the deep proteome in well-defined sets of ovarian tumors, FIGO stage I, Type 1 (low-grade serous, mucinous, endometrioid; n=9), Type 2 (high-grade serous; n=9), and benign serous (n=9) using TMT-LC-MS/MS. We evaluated new bioinformatics tools in the discovery phase. This innovative selection process involved different normalizations, a combination of univariate statistics, and logistic model tree and naïve Bayes tree classifiers. We identified 142 proteins by this combined approach. One biomarker panel and nine individual proteins were validated in cyst fluid and serum: transaldolase-1, fructose-bisphosphate aldolase A (ALDOA), transketolase, ceruloplasmin, mesothelin, clusterin, tenascin- XB, laminin subunit gamma-1, and mucin-16. Six of the proteins were found significant (p<0.05) in cyst fluid while ALDOA was the only protein significant in serum. The biomarker panel achieved ROC AUC 0.96 and 0.57 respectively. We conclude that classification algorithms complement traditional statistical methods by selecting combinations that may be missed by standard univariate tests.
2019-02-02 | PXD010939 | Pride
Project description:Transcriptional profiling of 19 ovarian tumors of 5 distinct histologic types (serous, endometrioid, clear cell, mucinous and small cell), to investigate similar and distinct biology associated with each histologic type. RNA from fresh-frozen ovarian tumor samples were individually hybridized to a pooled RNA from all 19 tumor cases
2014-01-17 | E-GEOD-49888 | biostudies-arrayexpress
Project description:In the current study we performed characterization of 18 different in vitro models of high-grade serous (HGSOC), low-grade serous (LGSOC), mucinous (MOC), endometrioid (ENOC) and clear cell (CCOC) carcinoma. This study seeks to fill in this gap by generating an integrative Ovarian Cancer Regulatory Atlas (OCRA) of 18 ovarian normal and cancer cells profiled for epigenomic, transcriptomic, chromatin state and chromatin looping signatures.
2024-03-18 | GSE261637 | GEO
Project description:Ovarian cancer is characterized by multiple structural aberrations; most are passenger alterations which do not confer tumor growth. Like many cancers, it is a heterogeneous disease and till date, the histotype-specific copy number landscape has been difficult to elucidate. To dissect the heterogeneity of ovarian cancer and understand the pathogenesis of its various histotypes, we developed an in silico hypothesis-driven workflow to identify histotype-specific copy number aberrations across multiple datasets of epithelial ovarian cancer. In concordance with previous studies on global copy number changes, our study showed similar alterations. However, when the landscape was de-convoluted into histotypes, distinct alterations were observed. We report here a comprehensive histotype-specific copy number landscape of ovarian cancer and showed that there is genomic diversity between the histotypes; some involving well known cancer genes and some novel potential driver genes. Besides preferential occurrence of alterations in some histotypes, opposite trends of alteration were observed; such as ERBB2 amplification in mucinous but deletion in serous tumors. The landscape highlights the need for identifying histotype-specific aberrations in ovarian cancer and present potential to tailor management of ovarian cancer based on molecular signature of histotypes. 56 samples containing the 4 histotypes were used for this study. It contained 12 clear cell carcinoma, 6 endometrioid adenocarcinoma, 2 mucinous adenocarcinoma, 5 mucinous-borderline tumors, 26 serous adenocarcinoma, and 5 serous-borderline tumors.
2012-10-25 | E-GEOD-30274 | biostudies-arrayexpress
Project description:Ovarian cancer is characterized by multiple structural aberrations; most are passenger alterations which do not confer tumor growth. Like many cancers, it is a heterogeneous disease and till date, the histotype-specific copy number landscape has been difficult to elucidate. To dissect the heterogeneity of ovarian cancer and understand the pathogenesis of its various histotypes, we developed an in silico hypothesis-driven workflow to identify histotype-specific copy number aberrations across multiple datasets of epithelial ovarian cancer. In concordance with previous studies on global copy number changes, our study showed similar alterations. However, when the landscape was de-convoluted into histotypes, distinct alterations were observed. We report here a comprehensive histotype-specific copy number landscape of ovarian cancer and showed that there is genomic diversity between the histotypes; some involving well known cancer genes and some novel potential driver genes. Besides preferential occurrence of alterations in some histotypes, opposite trends of alteration were observed; such as ERBB2 amplification in mucinous but deletion in serous tumors. The landscape highlights the need for identifying histotype-specific aberrations in ovarian cancer and present potential to tailor management of ovarian cancer based on molecular signature of histotypes. 56 samples containing the 4 histotypes were used for this study. It contained 12 clear cell carcinoma, 6 endometrioid adenocarcinoma, 2 mucinous adenocarcinoma, 5 mucinous-borderline tumors, 26 serous adenocarcinoma, and 5 serous-borderline tumors. Data was pre-processed and normalized with Hapmap JPT using the Affymetric Genotyping Console.
2012-10-25 | E-GEOD-30283 | biostudies-arrayexpress